Rick van der Lans, R20/Consultancy describes ways to increase BI agility with data virtualization. Rick demonstrates ways to build agile IT systems to support faster business decision making in business.

Data Integration Is the Biggest Bottleneck

Providing analytics and BI solutions with the data required has always been difficult, with data integration long considered the biggest bottleneck in any analytics or BI project. Complex data landscapes, diverse data types, new sources such as big data and the cloud are but a few of the well-known barriers.

For the past two decades, the solution has been to consolidate the data into a data warehouse, and provide users with tools to analyze and report on this consolidated data. However, data integration based on these traditional replication and consolidation approaches have numerous moving parts that must be synchronized. Doing this right extends lead times.

The Data Warehousing Institute confirms this lack of agility. Their recent study stated the average time needed to add a new data source to an existing BI application was 8.4 weeks in 2009, 7.4 weeks in 2010, and 7.8 weeks in 2011. And 33% of the organizations needed more than 3 months to add a new data source.